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» Detecting critical regions in multidimensional data sets
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EGITALY
2006
13 years 9 months ago
3D Data Segmentation Using a Non-Parametric Density Estimation Approach
In this paper, a new segmentation approach for sets of 3D unorganized points is proposed. The method is based on a clustering procedure that separates the modes of a non-parametri...
Umberto Castellani, Marco Cristani, Vittorio Murin...
ICMCS
2006
IEEE
141views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Coarse-to-Fine Pedestrian Localization and Silhouette Extraction for the Gait Challenge Data Sets
This paper presents a localized coarse-to-fine algorithm for efficient and accurate pedestrian localization and silhouette extraction for the Gait Challenge data sets. The coars...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
ICDT
2001
ACM
124views Database» more  ICDT 2001»
14 years 3 days ago
Mining for Empty Rectangles in Large Data Sets
Abstract. Many data mining approaches focus on the discovery of similar (and frequent) data values in large data sets. We present an alternative, but complementary approach in whic...
Jeff Edmonds, Jarek Gryz, Dongming Liang, Ren&eacu...
SIGMOD
2004
ACM
144views Database» more  SIGMOD 2004»
14 years 7 months ago
Diamond in the Rough: Finding Hierarchical Heavy Hitters in Multi-Dimensional Data
Data items archived in data warehouses or those that arrive online as streams typically have attributes which take values from multiple hierarchies (e.g., time and geographic loca...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...
BMCBI
2008
126views more  BMCBI 2008»
13 years 7 months ago
c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
Background: Computational methods for characterizing novel transcription factor binding sites search for sequence patterns or "motifs" that appear repeatedly in genomic ...
Katerina Kechris, Hao Li